1. Field of the Invention
An object of the present invention is a method for the reconstruction of images acquired by 3D experiments, especially in nuclear magnetic resonance (NMR). The method of the invention is especially applicable to NMR spectrometry or X-ray spectrometry. It can be transposed to image reconstruction computations used in tomodensitometry. Among all the reconstruction methods envisaged, the so-called 3 DFT reconstruction method is particularly referred to herein. Imaging methods using 3D acquisition, called 3D imaging methods, have many advantages as compared with two-dimensional or 2D acquisition methods with the selection of cross-sections in the bodies examined. In particular, they make it possible to propose thin, contiguous cross-sections with contours that are undistorted by supplementary steps in the method, which are required in order to define this cross-section. However, as compared with 2D methods, they have the disadvantage of requiring prohibitively lengthy periods for the acquisition and reconstruction of images.
2. Description of the Prior Art
Recent improvements in methods for the excitation of the magnetic moments of protons, known as steady state free precession (SSFP) methods, have considerably reduced 3D acquisition means. The time taken to present images then depends essentially on the time taken for reconstruction. Typically, there are known ways of showing images with resolutions that are substantially equal along two reference axes of the image. However, for an axis oriented in a direction perpendicular to the images, along the stack of these images, either a less efficient resolution is accepted (in the final analysis relatively thick slices, for example 1 cm slices, are chosen), or else the volume in which it is sought to make these images is restricted. Assuming, for example, that the body of a patient is stretched out in an NMR machine along an axis Z and that the aim is to make images of cross-sections of this body with resolutions in each image of, for example, 256.times.256 pixels, it is possible to accept, for example, a depiction of only eight images superimposed along the axis Z. This typical digital example shall be kept in the rest of the description of the invention because it gives a clear picture of the subject. Of course, the implications of the invention cannot be considered to be limited to this digital example.
The implementation of a 3DFT type imaging method calls for the application of excitation and measurement sequences which comprise, firstly, a radiofrequency electromagnetic excitation of the body to be examined and the measurement of a resulting NMR de-excitation signal and, secondly, the application of additional magnetic field gradient pulses (superimposed on the main magnetic field of the machine), for which the gradient directions are pre-determined with respect to the directions of the images of the sections to be obtained (in this case, cross-sections). It is known that, during the measurement of the NMR signal, a so-called read gradient is applied along a pre-determined axis of this type called a read axis. In general, the read axis is called the X-axis. During the 3D experiment, the field gradients applied to a so-called phase encoding axis (Y) and a cross-section selection axis (Z) assume different values from one sequence to another. For instance, there is a known method by which the cross-section selection gradient is fixed at a given value and for a given period during each sequence of a first series of sequences, while the phase encoding gradient value changes step by step during the first series of sequences. When the first series of sequences is acquired, the value of the cross-section selection gradient is incremented and the entire series of sequences is repeated. During the sequences of this other series, the phase encoding gradient again assumes the same series of values as for the first series of sequences. This series of frequencies is started again for as many times as it is sought to obtain images counted in the direction of stacking on the axis (Z). At the end of each series of sequences, 2D Fourier transform is used to compute the contributions to the final images. These contributions are thus acquired in each of these series of sequences. When all the contributions to the images have been computed, the image elements on all the images are computed by Fourier transform from these contributions to the images. Typically, each contribution image is defined on a space of 256.times.256 points. The computations of the final images then require, in the example, the performing of 8 .times.256.times.256=524288 one-dimensional Fourier transforms (or 256.times.256=65536 Fourier transforms) for which the number of computing points in each is small: it corresponds to a small number (eight) of series of sequences which itself corresponds to the small number of images sought to be depicted in the stack.
This method has many drawbacks. In particular, performing a very large number of Fourier transforms, with a small number of computing points, is ill suited to the vectorial processors used. For these processors are normally optimized to perform greater numbers of computing points. In practice, we thus arrive at an image reconstruction time of about 12 minutes in the example referred to above. Furthermore, the acquisition mode is such that, during this reconstruction period, no intermediate result is available: all the images are computed and available at the same time. This means that this waiting time cannot be used to interpret images which would be presented as and when they arise. Furthermore, in view of the number of data to be processed simultaneously, the addressing problems encountered to implement these reconstruction methods are great.
Finally, in the image, it is not always necessary to choose one and the same resolution along both axes. For example, it might be decided to produce images with 256.times.128 pixels. An additional problem would then be encountered. For, this reduction in resolution along one of the axes of the image, which reduces the measurements acquisition time by two, is counterbalanced by the fact that there are no standard programs in the vectorial processors used for reconstruction processing by 2D Fourier transform of non-symmetrical sets. Since there is no pre-recorded program available that works according to a fast algorithm, a specific algorithm has to be programmed. This specific algorithm cannot be as well suited to the machine as the fast algorithm for which the machine was itself designed. The result of this is that the expected time gain is not obtained.
An object of the invention is to remove the drawbacks referred to by modifying the organization of the acquisition of sequences as well as the organization of the computing of image reconstruction. In this computation, advantage is taken of the fact that, in one of the acquisition dimensions, the image resolution or the number of images is small. In practice, instead of first performing symmetrical 2D Fourier transforms (for example, 256.times.256) asymmetrical Fourier transforms (for example 8.times.256) are performed. However, vectorial processors are generally designed to work with a low-capacity fast memory and a high-capacity slower memory. In the invention it has been observed that the computation of highly asymmetrical 2D Fourier transforms makes it possible, by using the entire useful volume of the fast memory, to use vectorial processors to their maximum working speed. Subsequently, a third one-dimensional Fourier transform is performed with a large number of computing steps (256), and this large number too corresponds to a maximum use of the computing power of the vector processor. The result of this is that by making the processor work to its maximum capacity at all times, images are produced faster than by burdening it with an excessively large number of operations which, in particular, would be too simple for its capacity. A large number of to and fro movements between the processor and the slow memory are avoided.